Own and operate the data platform end to end, ensuring reliability, defining metrics, and providing technical leadership for the DGX Cloud program.
Compensation
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
Responsibilities
Own and operate the data platform end to end, including the pipelines that ingest, transform, and serve operational data to leadership and partner teams.
Ensure the reliability of those pipelines by setting and meeting targets for uptime, data freshness, and quality, and by leading incident response, root cause analysis, and prevention work.
Define, instrument, and report on operational success metrics such as SLIs/SLOs, pipeline latency, and data completeness, and use them to drive prioritization and continuous improvement.
Partner with customer teams to understand their data needs, translate those needs into platform capabilities and schemas, and set clear expectations for support and delivery.
Provide technical leadership by setting engineering standards, reviewing designs and code, mentoring engineers, and driving the platform roadmap.
Requirements
BS in Computer Science, Engineering, or a related field, or equivalent experience.
Data Scientist supporting global fraud analytics and scenario analysis within John Deere Financial’s Global Operational Analytics team.
Responsibilities
Maintain, assess, validate, and enhance risk-based models supporting Global Fraud detection, operational prioritization, and decision making
Develop and apply analytical models and methods to address evolving fraud risks and business needs
Analyze data to identify patterns, anomalies, emerging risks and opportunities to improve model effectiveness
Partner with Global Fraud, GOA leadership, and other business and technical stakeholders to understand business questions, define analytical requirements, and establish measures of success
Build and maintain repeatable data preparation, testing, model assessment, and validation processes
Requirements
Bachelor’s degree or equivalent experience in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Finance, Analytics, or a related quantitative field
Design, build, and maintain scalable data infrastructure and solutions that enable the collection, storage, and processing of large volumes of data across the organization.
Compensation
Minimum Starting Salary: CAD $112,000
Responsibilities
Design, develop, and optimize scalable data pipelines for ingesting, transforming, and distributing data across multiple systems
Build and maintain ETL processes to prepare, cleanse, and transform data from diverse sources
Automate workflows to improve reliability and reduce manual intervention
Configure and manage Azure-based data platforms and services for data processing and storage
Build and maintain data lakes, warehouses, semantic models, and analytics environments
Design, build, deploy, and maintain reliable, scalable, and governed research data pipelines and reusable data products supporting Research & Discovery, translational science, analytics, reporting, AI, and scientific decision-making.
Responsibilities
Design and maintain conceptual, canonical, logical, semantic, and physical data models for Research and Discovery data products.
Translate scientific, experimental, and business requirements into reusable enterprise information models.
Define core Research entities, attributes, identifiers, relationships, hierarchies, experimental context, events, and scientific business rules.
Establish canonical representations across laboratories, research sites, source systems, external providers, and data products.
Model structured, semi-structured, unstructured, and multimodal scientific data while preserving provenance and experimental context.
Lead design, development, and deployment of advanced computer vision and machine learning solutions for industrial and manufacturing applications.
Responsibilities
Design, develop, and deploy computer vision algorithms for detection, classification, segmentation, anomaly detection, and predictive analytics.
Build scalable machine learning and deep learning models using image, video, and multimodal sensor data.
Lead the complete data science lifecycle, including data collection, labeling, feature engineering, model training, validation, deployment, and monitoring.
Develop robust image-processing pipelines utilizing modern computer vision frameworks and cloud technologies.
Define data quality standards and establish model performance metrics to ensure production readiness.
Requirements
Master's degree in Data Science, Computer Science, Physics, or related field
Hands-on individual contributor role leading the design and build of a semantic data model for Xbox to ensure metric reliability across dashboards, scorecards, and AI agents.
Locations (3)
Redmond, Washington, United States
San Francisco, California, United States
New York, New York, United States
Compensation
The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Responsibilities
Lead the design and build of the XBOX semantic model: certified metric definitions, dimensions and metric views on Databricks.
Work with business and product owners to define and certify XBOX-wide metrics.
Senior Data Engineer responsible for owning and scaling the Audience Engine platform, including data ingestion, identity resolution, AI enablement, and pipeline optimization.
Responsibilities
Establish and own technical management of the Audience Engine
Reduce reliance on third-party vendors while maintaining high standards for platform reliability, uptime, and data integrity
Building and operationalizing agentic AI platforms, machine learning platforms, and data pipelines to power business use cases.
Compensation
The anticipated wage for this position is $69,000 - $165,000
Responsibilities
Design and build the engineering backbone for AI and ML systems, including orchestration frameworks, end-to-end data and model pipelines, serving infrastructure, and evaluation/monitoring.
Partner closely with data scientists to productionize models and agentic workflows.
Work with technical product managers, business, and field teams to bring solutions into secure and auditable applications.
Reuse infrastructure and patterns to ensure new business use cases ship faster and cheaper.
Build and operationalize agentic AI platforms (agent-to-agent orchestration, multi-agent workflow engines, tool/API integration).
Requirements
Master’s degree in Computer Science
Master’s degree in Computer Engineering
Master’s degree in Data Science
Master’s degree in a related quantitative or technical field
Build the checks that make a certified metric trustworthy: reconciliation against sources and existing reports, data quality and freshness monitoring, and alerts.
Make Xbox data ready for AI agents by providing metadata, lineage, documentation, and query patterns.
Bring data science judgment to the model: use telemetry analysis, design metrics for A/B experiment scorecards.
Requirements
Bachelor's Degree in Computer Science or related technical field
Data ScientistNewJohn Deere · Indaiatuba, Brazil